Published online Apr 15, 2026. doi: 10.4239/wjd.v17.i4.116772
Revised: December 24, 2025
Accepted: February 3, 2026
Published online: April 15, 2026
Processing time: 142 Days and 2.8 Hours
Diabetic kidney disease is the most common microvascular complication of type 2 diabetes mellitus (T2DM) and a leading cause of end-stage renal disease. Rapid estimated glomerular filtration rate (eGFR) decline (annual decline rate ≥ 5 mL/minute/1.73 m2) is a strong predictor of end-stage renal disease and cardio
To establish a comprehensive and accurate risk stratification system for patients with T2DM and kidney complications is of crucial importance for clinical deci
This retrospective cohort study enrolled 302 T2DM patients who attended our hospital from January 2021 to August 2024, with a minimum follow-up period of 12 months. Patients were divided into rapid decline group (≥ 5 mL/minute/1.73 m2, n = 89) and non-rapid decline group (< 5 mL/minute/1.73 m2, n = 213) based on annual eGFR decline rate. Least absolute shrinkage and selection operator regression combined with multivariate logistic regression was used to screen independent risk factors and construct a visualized Nomogram prediction model. eXtreme Gradient Boosting and Random Forest algorithms were employed for validation. Model performance was evaluated through receiver operating characteristic curves, calibration curves, and decision curve analysis, and the model’s generalizability was validated in an external validation cohort of 142 patients. Sensitivity analyses using the chronic kidney disease epidemiology collaboration equation were performed to assess the robustness of findings.
Multivariate analysis identified seven independent risk factors: Hemoglobin A1c ≥ 8.0% [odds ratio (OR) = 3.24, 95% confidence interval (CI): 1.76-5.98], baseline eGFR 45-59 mL/minute/1.73 m2 (OR = 4.17, 95%CI: 2.15-8.09), urine albumin-to-creatinine ratio ≥ 300 mg/g (OR = 5.63, 95%CI: 2.89-10.96), systolic blood pressure ≥ 140 mmHg (OR = 2.58, 95%CI: 1.42-4.69), serum uric acid ≥ 420 μmol/L (OR = 2.91, 95%CI: 1.53-5.54), anemia (OR = 2.34, 95%CI: 1.28-4.27), and non-use of renin-angiotensin-aldosterone system inhibitors (OR = 2.15, 95%CI: 1.18-3.92). The Nomogram model achieved an AUC of 0.876 (95%CI: 0.836-0.916) in the training set, with sensitivity of 81.5% and specificity of 79.8%. The external validation cohort demonstrated an AUC of 0.838 (95%CI: 0.768-0.908), showing good generalizability. Sensitivity analyses using chronic kidney disease epidemiology collaboration showed consistent results (AUC = 0.869, P = 0.42 vs modification of diet in renal disease-based model). The eXtreme Gradient Boosting model achieved a test set AUC of 0.889, but the difference from the nomogram model was not statistically significant (P = 0.285). The model demonstrated stable performance across different age, gender, and diabetes duration subgroups (AUC = 0.854-0.889) with non-significant interaction terms (all P interaction > 0.4). Compared with existing kidney failure risk equation 4, kidney failure risk equation 8, and Kidney Disease: Improving Global Outcomes stratification systems, our model showed significant advantages (P < 0.05) with net reclassification improvement of 0.385-0.428 and integrated discrimination improvement of 0.076-0.156 in external validation.
This work effectively developed a nomogram model with good discrimination, calibration, and clinical applicability for risk stratification of rapid eGFR drop among T2DM patients with indications of kidney involvement. The model integrates both established risk variables and new risk markers.
Core Tip: This study established a nomogram for risk stratification of rapid decline in estimated glomerular filtration rate in type 2 diabetes mellitus patients with established kidney involvement. The model integrates cardiovascular symptoms, metabolic indicators, and renal biomarkers, demonstrating high discrimination and strong clinical practicality. This tool enables identification of high-risk subgroups who would benefit from intensified monitoring and intervention to slow kidney function deterioration.